Joint calibration of a microscope traffic simulator and estimation of origin-destination flows

Abstract

Microscopic Traffic simulators can be effectively used to analyze various transportation strategies (especially ITS related). However, microscopic traffic simulators need to be calibrated in order to yield meaningful results. Calibration is the process of adjusting the model parameters to closely replicate the observed behavior. In this thesis, a module for joint calibration of a microscopic traffic simulator along with estimation of Origin- Destination (OD) flows has been developed. The developed framework takes into account the interactions between the various model parameters and the OD flows. An optimization-based framework has been proposed for the joint calibration of model parameters and estimation of dynamic OD flows. A systematic search approach based on the Box algorithm is adopted for calibration of the parameters. Depending on the problem size, a sequential or a simultaneous OD estimation algorithm is employed. Since the calibration of the parameters depends on the estimated OD flows and vice versa, the proposed framework is iterative. The developed framework has been implemented in MITSIMLab, a microscopic traffic simulation laboratory. Case studies on three networks with varying levels of complexity illustrate the potential of the calibration approach.